CN109782190A - Method for estimating the remaining useful life of a single battery or batch of batteries - Google Patents
Method for estimating the remaining useful life of a single battery or batch of batteries Download PDFInfo
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Abstract
The present invention relates to a kind of for estimating the method for the remaining life of battery the following steps are included: providing single battery；The circulation of multiple recharge-discharge is executed for single battery；In at least part charge-discharge process in the circulating cycle, the measurement for carrying out electrochemical impedance spectroscopy to single battery obtains the charge transfer resistance and superficial layer resistance of single battery by the fitting of equivalent-circuit model；Using obtained charge transfer resistance and superficial layer resistance and capacity is repeatedly recycled, the relationship between the capacity of single battery and cycle-index is established；And using the relationship between established capacity and cycle-index, predict the cycles left number of battery remaining power or battery.The present invention also proposes a kind of for estimating the method for the remaining life of a collection of battery.
Description
Technical field
The present invention relates to battery life predicting field, more particularly, to for estimating single battery or the single batch of battery
The method of remaining life.
Background technique
It is driven currently, lithium ion battery (LIB) is widely used in for new consumer device and the power supply of function tool, such as battery
Electric/hybrid automobile (EV/HEV), and the interim storage system for renewable energy.However, lithium ion battery
Performance can be influenced because of aging, environment and dynamic load due to degenerate over time.It is answered therefore, it is necessary to understand vehicle
Cell degradation behavior in monitors battery health, predicts the remaining life (RUL) of battery, take measures to slow down
It degenerates, and finally avoids unexpected catastrophic failure.In practical applications, accurately estimate cell health state (SOH) and service life
Ensure vehicle reliability in system level and improve battery manufacture in battery rank to play an important role.
For any extensive battery-driven electrical system, power management is to ensure that the best and reliable operation of battery pack
Essential part, such as the battery management system (BMS) in EV/HEV.By modeling appropriate, BMS can pass through tune
Economize on electricity source is using extending battery life and reduce opposite battery cost.Importantly, successfully cell degradation modeling can be with
BMS is helped to execute prediction, to detect the early signal of battery failures, to ensure safety.
For battery manufacturers, life prediction of the LIB under actual motion condition is for its product and vehicle or admittedly
It surely is more crucial problem for the reliable integrated and guarantee applied.However, with the exploitation of high quality battery, it is cell performance
The life cycle test data collection that can decline becomes costly and time-consuming.Therefore, it is desirable to which the acceleration based on cell degradation model is surveyed
Examination, to assess battery in scale at a reasonable time by application stress factor and by Data Extrapolation/be mapped to physical condition.
On the one hand, accurate Life Prediction Model, which may assist in conventional production practices, designs good quality control, so as to
Realize longer battery life.On the other hand, by quickly testing worst condition and process optimization, by eliminating early stage
Safety problem can greatly shorten new product development cycle and Time To Market.
Cell degradation process, including battery impedance increases, power attenuation and capacity attenuation may be derived from number of mechanisms, such as
Solid electrolyte interface (SEI) develops and active material variation.Material property, storage and cycling condition all can be to the uses of battery
Service life and performance produce a very large impact.On the other hand, the development of lithium ion battery is characterized by the parallel innovation in many fields.Often
When secondary change battery design or other parameters, it is necessary to reappraise service life and cycle performance.It can therefore, it is highly desirable to develop
Predict material or battery design variation to the model of the potential impact of cell degradation behavior.
Currently, having estimated baitery age level using different methods.According to hypothesis and mathematical method, they can divide
For five classes:
Analysis model with empirical fit: this is a kind of empirical method based on data, as a large amount of from real as possible
The data tested, with assessment or predictive estimation value.The main problem of these methods is a lack of the accuracy of data and measurement.
Statistical method: these methods do not need any priori knowledge about Aging mechanism, not about the vacation of the factor yet
If.Nor need chemically or physically equation.However, the shortcomings that this method is to need mass data could be effectively.
Model based on performance: performance model depends on battery types, cannot be directly extended to other batteries.It estimates
Aging under controlled case simultaneously shows good, but its all degradation mechanism that can not occur during the simulated battery service life.Therefore, should
Model can be considered as semiempirical model.
Model based on equivalent circuit: as electrical equipment, in the case where not knowing detailed structure, LIB behavior can be with
It is presented by the equivalent circuit comprising resistor, capacitor and inductor.Parameter identification can be directly by measurement or by equivalent
Circuit model is carried out from more complicated method.This method is also semiempirical type.
Electrochemical model: the purpose of these methods is to understand the specific physics occurred in battery use process and change in depth
Learn phenomenon.The ultimate challenge of physical model first is that the result between atom method and macromodel is connected.
In short, can be used many different types of from simple empirical data model of fit to physics/electrochemical analysis
Method is horizontal to estimate to have the cell degradation of different characteristics.All existing methods are required in precision of prediction and modeling complexity
Between weighed.Up to the present, most of researchs all concentrate on a specific aging mechanism or a specific modeling
It is horizontal.
In this application, for the advantage of several models of combination different phase, one is proposed from equivalent circuit mould
The semiempirical of type and statistical method models solution, solves choosing for operation difficulty, precision and predictive ability in a balanced fashion
War.
Summary of the invention
Based on this prior art, it is an object of the present invention to provide efficient, relatively accurate remaining battery lifes
Prediction technique and a collection of battery remaining life prediction technique.
The present invention proposes a kind of for estimating the method for the remaining life of battery, comprising the following steps:
Single battery is provided；
The circulation of multiple recharge-discharge is executed for the single battery；
In at least part charge-discharge process in the circulation, electrochemical impedance is carried out to the single battery
The measurement of spectrum obtains the charge transfer resistance and superficial layer resistance of single battery by the fitting of equivalent-circuit model；
Using obtained charge transfer resistance and superficial layer resistance and capacity is repeatedly recycled, the single battery is established
Capacity and cycle-index between relationship；And using the relationship between established capacity and cycle-index, predict battery
The cycles left number of residual capacity or battery.On the one hand, the capacity of battery and charge transfer resistance and superficial layer resistance it
Between relationship be certain functional relation.
On the one hand, such as following formula of the relationship between the capacity of battery and charge transfer resistance and superficial layer resistance (1)
It is shown:
Capacity=Aexp (Bn) R2+C·exp(D·n)·R3+E (1)
Wherein, capacity indicates the capacity of battery, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate charge and discharge
The number of the circulation of electric process, A, B, C, D and E are to obtain coefficient by fitting.
On the one hand, multiple recharge-discharge is executed for the single battery at room temperature or at temperatures greater than room temperature
Circulation.
On the one hand, the single battery is the lithium ion battery with positive electrode and negative electrode material.
On the one hand, the positive electrode is selected from LiCO2、LiNiO2、LiNixMnyO2、Li1+zNixMn-yCo1-x-yO2、
LiNixCoyAlzO2、LiV2O5、LiTiS2、LiMoS2、LiMnO2、LiCrO2、LiMn2O4、LiFeO2And combinations thereof, wherein each x
It independently is 0.3 to 0.8；Each y independently is 0.1 to 0.45；Each z is independently 0 to 0.2, and the wherein cathode
Material be selected from graphite, soft carbon, hard carbon, silicon, oxyalkylene silicon, Si-C composite material, Li-Ti oxide and and combinations thereof.
On the one hand, in the charge-discharge process of the single battery, it charge to using constant current given
Voltage then discharges to the single battery using the constant current.
On the one hand, in the charge-discharge process of the single battery, it charge to using constant current given
Voltage, then continue to charge to the single battery using the given voltage as constant voltage, until the single battery
Electric current be down to constant current, then discharged using the constant current battery.
On the one hand, it is linear relationship between the capacity of battery and charge transfer resistance and superficial layer resistance or is index
Relationship is exponential relationship between the capacity and cycle-index of battery.
On the one hand, in the cyclic process, every in the charge-discharge process of the circulation of given number, one is carried out
The measurement of secondary electrochemical impedance spectroscopy.
On the one hand, the relationship between charge transfer resistance and superficial layer resistance and cycle-index is linear relationship.
On the one hand, the relationship between charge transfer resistance and superficial layer resistance and cycle-index expression is following formula
(2) it is fitted:
R2=an+b R3=cn+d (2)
Wherein, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate the cycle-index of charge-discharge process,
A, b, c and d are coefficient.
On the one hand, the relationship between charge transfer resistance and cycle-index is linear relationship, superficial layer resistance and circulation
Relationship between number is exponential relationship.
On the one hand, the relationship between charge transfer resistance and superficial layer resistance and cycle-index expression is following formula
(3) it is fitted:
R2=an+b R3=exp (cn+d) (3)
Wherein, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate the cycle-index of charge-discharge process,
A, b, c and d are coefficient.
The present invention also proposes a kind of for estimating the method for the remaining life of a collection of battery, comprising the following steps:
Multiple batteries are selected from a collection of battery；
The remaining life for being as previously described for estimation single battery is executed for each battery in the multiple battery
Method；
The remaining life of the single battery of prediction is analyzed using the method for statistical distribution, it is pre- to obtain
The a collection of battery remaining power of battery or the cycles left number of battery surveyed.
On the one hand, a collection of battery is the commercial identical material system of battery manufacture and treatment conditions while manufacturing
Battery.
On the one hand, the statistical distribution be selected from Weibull distribution, exponential distribution, logarithm normal distribution, normal distribution and
A combination thereof.
On the one hand, it is carried out by remaining life of the following Weibull equation (4) to the single battery of prediction
Analysis:
Wherein, f (t) is the probability density function in the service life of battery, and t indicates battery life, and η is scale parameter, β table
Show form parameter.
On the one hand, the scale parameter is obtained according to stress factor using service life stress model.
On the one hand, the stress factor is selected from temperature, humidity, is charged and discharged multiplying power, is charged and discharged voltage, electric discharge
Depth, charged state and combinations thereof.
On the one hand, the service life stress model be selected from Arrhenius model, Eyring model, inverse power law model,
Coffin-Manson relationship, temperature-humidity relationship, the non-thermal relationship of heat, general Eyring relationship and combinations thereof.
On the one hand, using the Arrhenius service life stress model as shown in following formula (5) by the temperature stress factor with
Scale parameter is associated, to be further associated with battery life:
Wherein, T indicates temperature, and η (T) is the scale parameter obtained according to temperature T, and F is pre-exponential factor, and G is activation energy.
It, can be simultaneously using the method for the remaining life for estimating single battery and single batch of battery of the invention
Meet the challenge of operation difficulty, precision and predictive ability, can greatly reduce circulation time, while can control forecasting well
Error.
Detailed description of the invention
In the detailed description of the following drawings, non-limiting embodiment and its feature and further are described by means of attached drawing
The advantages of.
Fig. 1 shows the equivalent-circuit model of 18650 proposed cylindrical batteries.
Fig. 2A and 2B shows the nyquist diagram of the battery for the different recurring numbers tested under room temperature (22 DEG C).Wherein,
Fig. 2A shows the nyquist diagram of every 150 circulating repetitions measurement full battery (18650 cylinder LCO | C battery)；Fig. 2 B shows
The nyquist diagram of the 3 electrode button cells re-assemblied in the state of new of 100 circulations and 500 circulations out.
Fig. 3 A and Fig. 3 B, which are respectively illustrated, to be depended on for 18650LCO | what C lithium ion battery recycled under normal circulation
The number of cycles of different batteries extracts charge transfer resistance and superficial layer resistance (+0.5C/- from the equivalent-circuit model of proposition
0.5C, 22 DEG C of temperature).
Fig. 4 A- Fig. 4 G shows the capacity prediction of the battery at circulation 500 times, is shown from circulation 500 to circulation
800 prediction error.
Fig. 5 shows the NMC for every 50 recurring numbers tested under room temperature (22 DEG C) | the nyquist diagram of C battery.
Fig. 6 A- Fig. 6 B is shown depending on 18650NMC | the different batteries that C lithium ion battery recycles under normal circulation
Recurring number extracts charge transfer resistance and superficial layer resistance (+0.5C/-0.5C, temperature 22 from the equivalent-circuit model of proposition
℃)。
Fig. 7 A- Fig. 7 G shows the capacity prediction result of the battery at circulation 300 times.
Fig. 8 A- Fig. 8 B shows the LCO of selection | and C battery is with discharge-rate 1C and 2C electric discharge, and battery is in period 200 and week
Capacity prediction result at phase 300.
Fig. 9 A- Fig. 9 C shows the LCO depending on stress factor (discharge-rate 1C and 2C) | the distribution of C battery life.
Specific embodiment
Hereinafter, it brief description of the figures the invention will be described in more detail in the attached drawing.
The present invention provides a kind of mixed models for health state of lithium ion battery prediction, including are used for lithium-ion electric
The equivalent-circuit model and statistical method of pond life prediction and battery selection.The model can be used for single battery or a collection of battery
Life prediction.The model is counted by the understanding to physical and chemical process using the advantage of the adaptability of not homologous ray in real time
It is predicted according to updating with dynamic operation.Mixed model is utilized based on selected existing method, including experience, statistics and physical method
Diversified operating mode and operating parameter, it is intended to realize forecasting accuracy, model simplicity and various battery-driven electric power
Balance between the ability of application.Prediction proposed by the present invention is a multistage modeling process.
Here, modeling solution from equivalent-circuit model and statistical method exploitation semiempirical.Equivalent circuit method uses
Resistor, capacitor and inductor simulate the equivalent circuit for studying battery behavior, unrelated with particular type of battery.It can
By technology appropriate (such as electrochemical impedance spectroscopy/EIS) by circulation rapid survey frequency dependence resistance value (including real part and
Imaginary part).The superficial layer resistance and charge transfer resistance that the equivalent-circuit model proposed by fitting extracts can be used for predicting capacitor
The basic trend of battery status change during device is decayed.In addition, by empirical method determine capacitor and resistance (including superficial layer and
Electric charge transfer) between correlation.Finally, relevant parameter is used to predict the service life of battery.By increase data volume and continuously
Model correction, mixed model can provide high precision of prediction for cell health state, and for given battery types and operation
Agreement provides the RUL ability of estimation.
In a kind of hybrid modeling method such as following implementation for lithium ion battery life prediction proposed by the present invention
It is described.Hybrid modeling method is applicable not only to single lithium ion battery, is also applied for a collection of lithium ion battery.The modeling proposed
It can also be used to select similar battery from big group sample together with other standards.
(1) life prediction of single-cell lithium-ion battery
Electrochemical impedance is response of the electro-chemical systems (battery) to current potential is applied.The frequency dependence of the impedance can disclose
Potential chemical process.Electrochemical impedance spectroscopy (EIS) is widely used as the standard characterization technique of many materials system and application, example
Such as burn into plating, battery, fuel cell.The frequency dependence resistance data of retrieval can be fitted equivalent-circuit model to pass through
It is fitted equivalent-circuit model and obtains superficial layer resistance and charge transfer resistance.The equivalent circuit of EIS data is modeled for passing through root
Impedance data is modeled according to the circuit being made of ideal resistor (R), capacitor (C) and inductor (L) to extract electrification
The physically significant characteristic of system.Divide over time and space because true battery system not necessarily ideally has
The process of cloth, so special circuit elements are commonly used.These include broad sense constant phase element (CPE) and Warburg element
(ZW).Warburg element is used to indicate the diffusion impedance of battery.The generalized equivalent circuit element proposed for single battery
As shown in Figure 1.For cylindrical battery, the almost vertical left tail portion of EIS figure is due to inductance caused by winding.Of the invention
In model, circuit includes a resistance and an inductance element, it is by inductor and resistor (L1And R1) composition.Active particle
The variation of middle capacitor is expressed as constant phase element (CPE1), with charge transfer resistance (R2) and indicate that Li ion is spread in particle
Warburg resistor coupled in parallel.Capacitor in superficial layer is expressed as CPE2, with superficial layer resistance (R3) in parallel.R4Indicate electrolysis
Liquid, adhesive, collector and contact resistance Ohmic resistance.
For battery, capacity for unit, stores available energy in the battery for quantifying with milliampere hour (mAh)
Amount.However, the capacity of current lithium ion battery is irreversibly reduced with charge and discharge cycles number and storage time.
The capacity and charge transfer resistance R of lithium ion battery2With superficial layer resistance R3It is related.In the charge and discharge process of battery
In, with the increase of the cycle-index of charge and discharge process, electrochemical reaction for several times is had occurred in battery, with the hair of electrochemical reaction
Raw, the resistance of lithium ion battery increases, and therefore battery capacity reduces.Such as room temperature at a temperature of and certain voltage
In range, using the multiplying power of charging and discharging, by establishing the variation of impedance-capacity-mapped relationship reaction cell capacity and impedance
Relationship.There are certain functional relation between the capacity and charge transfer resistance and superficial layer resistance of battery, which includes
But it is not limited to the form as shown in following formula (1).
Capacity=Aexp (Bn) R2+C·exp(D·n)·R3+E (1)
Wherein, capacity indicates the capacity of battery, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate charge and discharge
The number of the circulation of electric process, A, B, C, D and E are coefficient.
Using which, the capacity of battery known first, such as 100% (service life) capacity when, charge and discharge is carried out to battery
Electricity, also, for example measured by EIS, obtain the resistance R of battery2And R3.It is fitted, obtains followed by above formula (1)
Coefficient A, B, C, D and E.In prediction battery capacity in use, can predict single battery using these parameters A, B, C, D and E
Residual capacity, such as prediction single battery 80% (i.e. service life) capacity keep cycles left number.
The charge transfer resistance R of battery2With superficial layer resistance R3It can be measured and be obtained by EIS, also can use following public affairs
Formula (2) or (3) tracking obtain, that is, using linear function with multiple circulations, such as hundreds of circulations, are fitted R2And R3。
R2=an+b R3=cn+d (2)
R2=an+b R3=exp (cn+d) (3)
Wherein, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate the number of the circulation of charge and discharge process,
A, b, c and d are coefficient.
In the present embodiment, it is measured by EIS, obtains the resistance R in multiple periods2And R3, followed by above formula
(2) or (3), obtaining a, b, c and d is coefficient.Then, during predicting battery capacity, above formula (2) or (3) are utilized
Obtained coefficient a, b, c and d obtains the R after n times circulation2And R3。
It is, of course, also possible to by analysis equation, such as the modes such as linear analysis or index analysis, or pass through statistical method,
Such as in the way of particle filter, gray level model etc., to track circuit element, to obtain corresponding charge transfer resistance and table
Surface layer resistance.
It can be seen that in an application of the invention, single battery recycles in several circulations under certain conditions.It is recycling
Period repeats EIS measurement in several discontinuous circulations.EIS spectrum is obtained by being fitted each measurement, can be extracted
Circuit element obtains charge transfer resistance and superficial layer resistance, and is drawn according to cycle-index.Then, during cell degradation
Charge transfer resistance and the variation tendency of superficial layer resistance can use certain analysis equations (such as linear or index etc.) or system
Meter method (such as particle filter, gray model etc.) fitting.Then, carry out capacity-mapped with obtain capacity and cycle-index it
Between relationship.Finally, the capacity of any number of cycles of established Relationship Prediction can be used.
(2) life prediction of a collection of lithium ion battery
In order to which the hybrid modeling method proposed is further applied to a collection of battery, will prepare to come from identical manufacturing process
One group of selected target battery sample, for ensuring consistency after screening step.From will be with a batch of battery
It is recycled under identical operating condition.This batch of battery is the commercial identical material system of battery manufacture and treatment conditions while manufacturing
Battery.In order to accelerate battery life predicting process, can modify for certain factors with the acceleration tested.Acceleration follows
Ring test will be carried out by stress factors, such as: increase discharge-rate or improves temperature to accelerate the time of test.It is answered in difference
Under power level for different stress factors extracted by being fitted the suggestion equivalent-circuit model of each battery superficial layer resistance and
Charge transfer resistance.For specific stress factor and specific stress level, superficial layer resistance, charge transfer resistance and capacity
Obey Weibull distribution.The superficial layer resistance depending on cycle-index, charge transfer resistance are obtained by Weibull analysis statistics
With the average value of capacity.In addition, passing through empirical method establishment average size and the average resistance including superficial layer and electric charge transfer
Between correlation.Finally, relevant parameter is used to predict the service life of battery.Different stress levels (at least two stress levels)
Bimetry be used for infer any stress level batch battery service life.
Firstly, having selected some batteries as representative from a collection of battery.Above-mentioned single battery Prediction program is for predicting
The service life of each battery.The bimetry of single battery obeys certain statistical distributions (such as Weibull distribution) of the batch, and
And the service life of the battery of the batch can be obtained by statistical analysis.Statistical distribution is selected from Weibull distribution, exponential distribution, logarithm
Normal distribution, normal distribution and combinations thereof, are illustrated by taking Weibull distribution as an example below.
In order to improve forecasting efficiency and shorten circulation time, using different stress factors, such as discharge-rate, temperature into
Row accelerated test.For any stress factors, at least need to recycle under two stress levels.
For each Sample Cell in every group, it is utilized respectively the longevity that above-mentioned formula (1) prediction obtains each Sample Cell
Life (i.e. battery can also charge and discharge cycles number).Then, each group of service life is fitted by following Weibull equation (4)
Probability density function:
Wherein, f (t) is the probability density function in the service life of battery, and t indicates battery life, and η is scale parameter, β table
Show form parameter.
For using temperature as stress factor, battery life is calculated.Sample Cell is divided into two groups.Two groups in difference
At a temperature of recycle, such as recycled at 35 DEG C and 45 DEG C respectively.Then temperature is answered in selection service life stress model (Arrhenius)
The power factor associates as follows with scale parameter.
Wherein, T indicates temperature, and η (T) be the scale parameter obtained according to temperature T, F for pre-exponential factor (also referred to as frequency because
Son), G is activation energy, can be considered as constant when range of temperature is little.
In order to which the temperature stress factor associates with battery life, above formula (4) and (5) are combined into obtained combination
Model can be write as:
It is fitted using the service life of above formula (6) and multiple Sample Cells of formula (1).It is hereby achieved that any
At a temperature of a collection of battery life, also in the case where available random capacity, the remaining life of this batch of battery.
In the still identical situation of failure mode, the parameter retrieved can be used under any temperature (such as: room temperature)
Infer the service life of this batch of circulating battery.Testing time will greatly shorten.
In addition, also having other batteries selection based on the life-span prediction method proposed.For the ease of battery manufacturers
In battery quality control and second-hand battery battery classification and recycle, above-mentioned life-span prediction method can with other mark
Standard is used together, to use the minimum testing time to select the battery with conditions of similarity from a large amount of samples.Other standards can wrap
It includes but is not limited to the following contents:
1) weight, size
2) resistance: it is charged and discharged the moment
3) it capacity: is averaged
4) voltage: open circuit and closed loop
5) charging and discharging curve: area, shape etc.
6) the capacity ratio between constant-current charge and constant-voltage charge
7) transformation temperature on dQ/dV curve
8) etc.
It, can be while using prediction technique of the invention using such as the battery quality control in battery manufacturers
The service life of upper normative forecast a batch lithium ion battery.Thus, it is possible to substantially reduce the testing time for obtaining every batch of battery life.For
Second-hand battery is classified and is recycled, the life-span prediction method of single lithium ion battery can be with other selection criteria one
It rises and uses, to select that there is the battery of similar health status.Battery pack comprising similar battery can be used for certain applications.Use foot
The different batteries (such as different material systems, different treatment conditions etc.) of enough amounts.Also it can establish database, based on number
It will be more effective according to the battery selection in library.
It is further described by method of the following example to prediction battery life of the invention.
Example 1
With LiCoO3| illustrate single battery life predicting for C system.Selection has similar primary condition (weight, exchange
Electric internal resistance and discharge capacity) battery recycled.Room temperature is set as 22 DEG C, and voltage range is 2.75V to 4.35V, charging and
The multiplying power of electric discharge is 0.5C (1500mA).These batteries are recycled by S.O.P.: passing through constant current first
Battery is charged to 4.35V by (1500mA), then continues to charge the battery using the 4.35V as constant voltage, until electric current
It is down to 60mA, electric discharge is then carried out to battery by constant current (1500mA) until the voltage of battery is down to 2.75V.For
The capacity retention ratio of 0.5C/0.5C group, most of batteries is down to 80% or less after 1000 circulations.
In the present invention, electrochemical workstation PAR VersaSTAT 3 is measured for EIS.Due to 18650 cylindrical batteries
Internal driving is minimum (~50m Ω), uses constant current EIS mode.EIS measurement is disturbed in depth of discharge (DOD) 50%, 100mA
It is carried out under dynamic and 10kHz-10mHz frequency.Every 150 circulations, in the LiCoO of DOD 50%2| 18650 cylindrical battery of C is how
Impedance response in Qwest's figure is as shown in Figure 2 A and 2B.30 periods, impedance data only shows a semicircle.Later, half
Circle becomes larger, and is gradually divided into two semicircles.Meanwhile the EIS as caused by anode and cathode is also shown in fig. 2b.It is obvious that cathode
(material such as graphite) is bigger to total resistance contribution of new battery.After circulation, LiCoO2(i.e. positive, material such as LCO) just
It is extremely increasing to the contribution of the all-in resistance of battery.Assuming that the EIS result of 18650 cylindrical batteries is dominated by positive (LCO).Newly go out
Existing semicircle is contributed by the solid-electrolyte interphace (SEI) occurred on the surface LCO.
The typical nyquist diagram of the cylindrical battery obtained after every 150 circulations is as shown in Figure 2 A.It follows at the last one
Impedance response is measured under the 50%DOD of ring.By EIS data, the semicircle observed is divided into two semicircles.During circulation
The radius of two semicircles increases, this shows that the polarization resistance of each part is synchronous and increases.Therefore, the variation for studying resistance may have
Help understand capacity attenuation mechanism.By being fitted equivalent-circuit model presented above, charge transfer resistance and superficial layer are extracted
Resistance and the cycle-index for being directed to different batteries, obtain the pass between charge transfer resistance and superficial layer resistance and cycle-index
System, as shown in figs.3 a and 3b.Charge transfer resistance and superficial layer resistance show the High Linear correlation with recurring number.This embodiment party
Using linear function with 500 circulation fitting charge transfer resistances and superficial layer resistance in formula.The formula of circuit element tracking is such as
Under:
R2=an+b R3=cn+d (2)
Wherein, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate the number of the circulation of charge and discharge process,
A, b, c and d are coefficient.
Using general Global Algorithm.Fitting result is as shown in table 1, and which describe the tracking of the circuit element of LCO system
Fitting result, #7, #13, #33, #44, #46, #69, #70 are for marking tested battery, R2Indicate charge transfer resistance, R3It indicates
Superficial layer resistance.
Table 1
The capacity of lithium ion battery can irreversibly be reduced with charge and discharge cycles number.It is well known that battery capacity
It reduces related with resistance.Shown in the relationship established between resistance and capacity such as formula (1).The R obtained using fitting2And R3, utilize
The value of A, B, C, D, E of n times circulation is calculated in formula (1).
At 500 circulations, the fitting result of the capacity-mapped of LCO system is as shown in table 2, wherein.Prediction result is as schemed
Shown in 4A-4G, wherein representing the relationship between the number of cycles of prediction and the battery capacity of holding.Battery is carried out further
Experiment the result shows that, the holding capacity compared with the battery capacity of the actual measurement after 800 circulations, after 800 circulations
Predict error within 5%.
| #7 | #13 | #33 | #44 | #46 | #69 | #70 | |
| A | 9.34 | 6.48 | 4.63 | 13.16 | 10.63 | 8.78 | 11.15 |
| B | -0.05372 | -0.03398 | -0.07987 | -0.001413 | -0.002729 | -0.02260 | -0.003229 |
| C | 10.22 | 41.22 | 20.92 | 12.65 | 18.60 | 15.60 | 4.29 |
| D | -0.005398 | -0.005777 | -0.009861 | -0.03165 | -0.008356 | -0.001742 | -0.02570 |
| E | 0.85 | 0.71 | 0.84 | 0.75 | 0.75 | 0.69 | 0.82 |
Table 2
Example 2
In this example, positive electrode is changed to Li (NixMnyCoz)O2(NMC) system, with pre- for the single battery service life
It surveys.The battery with similar primary condition (weight, alternating current internal resistance and discharge capacity) is filtered out for recycling.In the example
In, room temperature is set as 22 DEG C, and certainly in the case where needing to accelerate, temperature can also be promoted to accelerate to test, such as be promoted to
30 DEG C, 40 DEG C etc..Experimental voltage range is 2.75V to 4.2V.The multiplying power of charging and discharging is 0.5C (1300mA).Shielding electricity
Pond is recycled by S.O.P.: being charged to 4.2V by constant current (1300mA) first, is recycled constant voltage further
Then charging discharges to battery by constant current (1300mA) until electric current is down to 60mA, up to voltage to 2.75V.
For 0.5C/0.5C group, most of battery capacity conservation rates are down to 80% or less after 400 circulations.
According to the present invention, electrochemical workstation PAR VersaSTAT 3 is measured for EIS.Due to 18650 cylindrical batteries
Internal driving is very small (~50m Ω), therefore uses constant current EIS mode.EIS measurement depth of discharge (DOD) 50%,
It is carried out under 100mA disturbance and 10kHz-10mHz frequency.Every 50 are recycled, in the NMC of DOD 50% | C 18650 is cylindrical
Impedance response in the nyquist diagram of battery is as shown in Figure 5.
As shown in the typical nyquist plot for the cylindrical battery of Fig. 5 obtained after every 50 circulations, at the last one
Impedance response is measured under the 50%DOD of circulation.EIS data shows that a semicircle is divided into apparent two semicircles, with LCO phase
Together.The radius of two semicircles increases during circulation, this shows that the polarization resistance of each part is synchronous and increases.It is mentioned above by being fitted
Equivalent-circuit model out extracts charge transfer resistance and superficial layer resistance, and the electricity of different batteries is represented in Fig. 6 A-6B
Relationship between lotus transfer resistance and superficial layer resistance and recurring number.Wherein visible charge transfer resistance and superficial layer resistance are shown
With the High Linear correlation of recurring number.In the example, existed using the linear function of following formula (3) and the function about index
Fitting charge transfer resistance and superficial layer resistance in 300 periods.
R2=an+b R3=exp (cn+d) (3)
Wherein, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate the number of the circulation of charge and discharge process,
A, b, c and d are coefficient.
Using general Global Algorithm.The fitting result of the circuit element tracking of NMC is as shown in table 3 in the present embodiment, #24, #
26, #28,29, #30, #33, #34 are for marking tested battery, R2Indicate charge transfer resistance, R3Indicate superficial layer resistance.
Table 3
Fitting for charge transfer resistance and superficial layer resistance, the R that can be obtained according to measurement2And R3To above two
Kind formula carries out analysis and the Fitting Calculation, it follows that one of more suitable fit approach, and in subsequent prediction process
In carry out using.
With the difference of charge and discharge cycles number, the capacity of lithium ion battery can be reduced irreversibly.It is well known that battery
The reduction of capacity is related with resistance.Shown in the relationship established between resistance and capacity such as formula (1).The R obtained using fitting2With
R3, the value of A, B, C, D, E of n times circulation are calculated using formula (1).
In 300 circulations, the fitting result of the capacity-mapped of NMC system is as shown in table 4.Prediction result such as Fig. 7 A-7G
It is shown, wherein indicating the relationship between cycle-index and the retention capacity of battery.The result shows that the capacity of 500 circulations is kept
Rate predicts error within 5%.
| #24 | #26 | #28 | #29 | #30 | #33 | #34 | |
| A | 2.6191 | 2.6835 | 3.0241 | 1.8795 | 3.0804 | 2.6634 | 1.7284 |
| B | -0.02771 | -0.02827 | -0.05296 | -0.03923 | -0.03053 | -0.03785 | -0.04176 |
| C | -0.0755 | -0.1551 | -0.09089 | -0.6458 | -0.3068 | -0.5873 | -0.3275 |
| D | 0.01042 | 0.007889 | 0.01023 | 0.003251 | 0.005651 | 0.004186 | 0.005226 |
| E | 0.9745 | 0.9786 | 0.9811 | 0.9870 | 0.9819 | 0.9815 | 0.9884 |
Table 4
Example 3
In this example, the average life span of a collection of battery is determined using loop test is accelerated.Pass through discharge-rate (1C electric discharge
Multiplying power and 2C discharge-rate) design Acceleration study.Two groups of batteries are obtained from identical manufacturing process and screening process.Two groups of electricity
Pond is recycled respectively with the different discharge-rates of 1C and 2C.Each selected battery as test can be recycled by 300 times
With the prediction of single battery prediction technique.Utilize each quilt for two groups of batteries that the method for above-described measurement single battery measures
The service life for surveying battery lists in table 5, wherein first four battery, i.e., uses labeled as the battery of #111, #113, #114 and #115
It recycles, rear four batteries, i.e., is recycled for 2C labeled as the battery of #119, #120, #122 and #228 in 1C.The two of classic predictive
A example as shown in figs. 8 a and 8b, wherein respectively indicating the cycle-index of #111 battery and #120 battery and the retention capacity of battery
Between relationship.
| Battery | It is practical | Prediction | Error |
| #111 | 616 | 631 | 2.4% |
| #113 | 462 | 429 | 7.7% |
| #114 | 719 | 729 | 1.4% |
| #115 | 562 | 600 | 6.3% |
| #119 | 426 | 488 | 12.7% |
| #120 | 440 | 491 | 10.3% |
| #122 | 293 | 357 | 17.9% |
| #228 | 346 | 371 | 6.7% |
Table 5
Then 1C and 2C used as two discharge rate levels predict the battery longevity under normal circulation condition (i.e. 0.5C)
Life.After the single battery capacity prediction result of each for obtaining above multiple tested batteries, Weibull function pair is utilized
The service life of the circulation of this batch of battery is predicted.General logarithmic linear (GLL) is fitted according to the prediction result of different stress levels
Model.Service life of this batch of battery under normal circulation is as shown in Figure 9A-9C.Compared with testing the service life under normal circulation, prediction
Error is can be controlled within 15%.And global cycle number can be reduced to 300 circulations from 1200 circulations.
Embodiment
It is 1, a kind of for estimating the method for the remaining life of single battery, comprising the following steps:
(1) the several circulations of single battery are recycled under certain condition；
(2) in cyclic process, every in the charge-discharge process of the circulation of given number, primary electrochemical resistance is carried out
The measurement of anti-spectrum；
(3) by being fitted each EIS, extracting equivalent-circuit component and being drawn according to cycle-index；
(4) track cell degradation during circuit component variations trend；
(5) capacity-mapped is carried out to obtain the relationship between capacity and cycle-index；
(6) capacity of any periodicity of established Relationship Prediction can be used.
2, according to method described in embodiment 1, the single battery is the lithium ion with positive electrode and negative electrode material
Battery, and wherein the positive electrode is selected from LiCO2、LiNiO2、LiNixMnyO2、Li1+zNixMn-yCo1-x-yO2、
LiNixCoyAlzO2、LiV2O5、LiTiS2、LiMoS2、LiMnO2、LiCrO2、LiMn2O4、LiFeO2And combinations thereof, wherein each x
It independently is 0.3 to 0.8；Each y independently is 0.1 to 0.45；Each z is independently 0 to 0.2, and wherein negative electrode material
Selected from graphite, soft carbon, hard carbon, silicon, oxyalkylene silicon, Si-C composite material, Li-Ti oxide and and combinations thereof.
3, according to method described in embodiment 1, by analysis equation (such as linear or index etc.) or statistical method (such as
Particle filter, gray level model etc.) track the circuit element.
4, according to method described in embodiment 1, the capacity-mapped is completed by analysis equation or statistical method.
It is 5, a kind of for estimating the method for the remaining life of a collection of battery, comprising the following steps:
(1) select some batteries as representative from batch；
(2) the life prediction process of single battery is carried out, using the method for previous embodiment 1 to predict each single battery
Service life；
(3) statistical distribution of the bimetry of single battery is determined；
(4) pass through the service life of statistical analysis this batch of battery of prediction.
6, the method according to embodiment 5, this batch of battery are the commercial identical material system of battery manufacture and processing item
The battery that part manufactures simultaneously.
7, the method according to embodiment 5, the statistical distribution are selected from Weibull distribution, exponential distribution, lognormal
Distribution, normal distribution and combinations thereof.
8, a kind of method for the remaining life that a collection of battery is estimated based on acceleration test, comprising the following steps:
(1) the identified sign factor and stress level are in the range of same battery degradation mechanism；
(2) cycle battery under different stress levels；
(3) the life prediction program of a collection of battery is carried out, using the method for previous embodiment 5 to predict each stress level
Under service life；
(4) service life-pressure model is selected, stress factors are associated with battery life；
(5) service life of this batch of battery recycled under any stress level of the prediction within the scope of same battery degradation mechanism.
9, the method according to embodiment 8, the stress factor are selected from temperature, humidity, are charged and discharged C- rate, fill
Electricity and discharge voltage, depth of discharge, charged state and combinations thereof.
10, the method according to embodiment 8, the service life stress model are selected from Arrhenius model, Eyring mould
Type, inverse power law model, Coffin-Manson relationship, temperature-humidity relationship, the non-thermal relationship of heat, general Eyring relationship and its group
It closes.
It, still can be to the embodiment described although the present invention is disclosed by reference to certain preferred embodiments
Many remodeling, change and change and its equivalent are made, without departing from the field of the invention and range.Therefore, present invention unawareness
Figure is limited to described embodiment, and broadest reasonable dismissal is provided according to the language of the attached claims.
Claims (21)
1. a kind of for estimating the method for the remaining life of battery, comprising the following steps:
Single battery is provided；
The circulation of multiple recharge-discharge is executed for the single battery；
In at least part charge-discharge process in the circulation, electrochemical impedance spectroscopy is carried out to the single battery
Measurement, by the fitting of equivalent-circuit model, obtains the charge transfer resistance and superficial layer resistance of single battery；
Using obtained charge transfer resistance and superficial layer resistance and capacity is repeatedly recycled, the appearance of the single battery is established
Relationship between amount and cycle-index；And using the relationship between established capacity and cycle-index, predict remaining battery
The cycles left number of capacity or battery.
2. the method according to claim 1, wherein the capacity of battery and charge transfer resistance and superficial layer resistance
Between relationship be certain functional relation.
3. according to the method described in claim 2, it is characterized in that, the capacity of battery and charge transfer resistance and superficial layer resistance
Between relationship such as following formula (1) shown in:
Capacity=Aexp (Bn) R2+C·exp(D·n)·R3+E (1)
Wherein, capacity indicates the capacity of battery, R2Indicate charge transfer resistance, R3Indicate that superficial layer resistance, n indicate charge and discharge
The number of the circulation of journey, A, B, C, D and E are to obtain coefficient by fitting.
4. method according to any one of claim 1-3, which is characterized in that at room temperature or in temperature above room temperature
The circulation of multiple recharge-discharge is executed for the single battery down.
5. method according to any one of claim 1-3, which is characterized in that the single battery is with positive electrode
With the lithium ion battery of negative electrode material.
6. according to the method described in claim 5, it is characterized in that, the positive electrode is selected from LiCO2、LiNiO2、
LiNixMnyO2、Li1+zNixMn-yCo1-x-yO2、LiNixCoyAlzO2、LiV2O5、LiTiS2、LiMoS2、LiMnO2、LiCrO2、
LiMn2O4、LiFeO2And combinations thereof, wherein each x independently is 0.3 to 0.8；Each y independently is 0.1 to 0.45；Each z
Independently 0 to 0.2, and wherein, the negative electrode material is selected from graphite, soft carbon, hard carbon, silicon, oxyalkylene silicon, silicon-carbon composite wood
Material, Li-Ti oxide and and combinations thereof.
7. method according to any one of claim 1-3, which is characterized in that the recharge-discharge mistake of the single battery
Cheng Zhong carries out it using constant current to charge to given voltage, then using the constant current to the single battery into
Row electric discharge.
8. method according to any one of claim 1-3, which is characterized in that the recharge-discharge mistake of the single battery
Cheng Zhong is carried out it using constant current to charge to given voltage, then is continued using the given voltage as constant voltage to institute
It states single battery to charge, until the electric current of the single battery is down to constant current, then utilizes the constant current pair
The single battery discharges.
9. method according to any one of claim 1-3, which is characterized in that in the cyclic process, every given
In the charge-discharge process of the circulation of number, the measurement of primary electrochemical impedance spectrum is carried out.
10. method according to any one of claim 1-3, which is characterized in that charge transfer resistance and superficial layer resistance
Relationship between cycle-index is linear relationship.
11. according to the method described in claim 10, it is characterized in that, charge transfer resistance and superficial layer resistance and cycle-index
Relationship between expression is following formula (2) fitting:
R2=an+b R3=cn+d (2)
Wherein, R2Indicate charge transfer resistance, R3Expression superficial layer resistance, the cycle-index of n expression charge-discharge process, a, b,
C and d is coefficient.
12. method according to any one of claim 1-3, which is characterized in that charge transfer resistance and cycle-index it
Between relationship be linear relationship, relationship between superficial layer resistance and cycle-index is exponential relationship.
13. according to the method for claim 12, which is characterized in that charge transfer resistance and superficial layer resistance and cycle-index
Relationship between expression is following formula (3) fitting:
R2=an+b R3=exp (cn+d) (3)
Wherein, R2Indicate charge transfer resistance, R3Expression superficial layer resistance, the cycle-index of n expression charge-discharge process, a, b,
C and d is coefficient.
14. a kind of for estimating the method for the remaining life of a collection of battery, comprising the following steps:
Multiple batteries are selected from a collection of battery；
It executes as of any of claims 1-13 for each battery in the multiple battery for estimating single electricity
The method of the remaining life in pond；
The remaining life of the single battery of prediction is analyzed using the method for statistical distribution, with what is predicted
A batch battery remaining power of battery or the cycles left number of battery.
15. according to the method for claim 14, which is characterized in that a batch battery is the commercial identical material of battery manufacture
The battery that material system and treatment conditions manufacture simultaneously.
16. method according to claim 14 or 15, which is characterized in that the statistical distribution is selected from Weibull distribution, refers to
Number distribution, logarithm normal distribution, normal distribution and combinations thereof.
17. method according to claim 14 or 15, which is characterized in that by following Weibull equation (4) to prediction
The remaining life of the single battery is analyzed:
Wherein, f (t) is the probability density function in the service life of battery, and t indicates that battery life, η are scale parameter, and β indicates shape
Shape parameter.
18. according to the method for claim 17, which is characterized in that obtain institute according to stress factor using service life stress model
State scale parameter.
19. according to the method for claim 18, which is characterized in that the stress factor is selected from temperature, humidity, charges and put
Electric multiplying power is charged and discharged voltage, depth of discharge, charged state and combinations thereof.
20. according to the method for claim 18, which is characterized in that the service life stress model be selected from Arrhenius model,
Eyring model, inverse power law model, Coffin-Manson relationship, temperature-humidity relationship, the non-thermal relationship of heat-, general Eyring
Relationship and combinations thereof.
21. according to the method for claim 18, which is characterized in that utilize the Arrhenius longevity as shown in following formula (5)
The temperature stress factor is associated by life stress model with scale parameter, to be further associated with battery life:
Wherein, T indicates temperature, and η (T) is the scale parameter obtained according to temperature T, and F is pre-exponential factor, and G is activation energy.
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